AI in Revenue Enforcement and Debt Management

1. Assess debt portfolios and identify cases requiring priority attention.
2. Use AI and analytical tools to support enforcement planning and debt recovery decisions.
3. Develop appropriate taxpayer engagement and payment monitoring strategies.
4. Strengthen case management, supervisory controls and recovery reporting.
5. Prepare a responsible AI implementation plan for enforcement and debt management operations.

1. Revenue Enforcement and Debt Management Foundations

• Examining the debt management lifecycle from liability confirmation and notification to recovery, resolution and closure.
• Defining responsibilities, approval requirements and coordination between registration, assessment, collections, enforcement and legal teams.

2. Debt Data Quality and Account Verification

• Reconciling assessments, payments, credits, penalties and adjustments to establish reliable outstanding balances.
• Identifying duplicate debts, allocation errors, disputed amounts and incomplete records before initiating recovery action.

3. Debt Portfolio Analysis and Segmentation

• Analysing debts by age, value, taxpayer category, payment history, dispute status and recovery stage.
• Distinguishing cases requiring correction, taxpayer assistance, further investigation or authorised enforcement.

4. AI-Assisted Risk Assessment and Case Prioritisation

• Using approved AI tools to summarise case histories and identify patterns requiring officer review.
• Developing transparent prioritisation criteria while checking data quality, false flags and the limitations of automated recommendations.

5. Taxpayer Engagement and Recovery Communication

• Preparing clear notices, reminders and follow-up messages that explain balances, required actions and available response channels.
• Using AI to assist communication drafting while verifying amounts, deadlines, tone and procedural accuracy.

6. Payment Arrangements and Compliance Monitoring

• Assessing payment proposals against verified information, institutional criteria and authorised approval procedures.
• Tracking instalments, missed payments and follow-up actions through structured registers and alerts.

7. Enforcement Planning and Interagency Coordination

• Preparing proportionate enforcement recommendations supported by verified debt records and documented case assessments.
• Coordinating authorised referrals with legal teams and relevant agencies while respecting taxpayer rights and review processes.

8. Debt Dashboards and Recovery Performance

• Building Excel-based dashboards to monitor debt ageing, collections, case progress, payment arrangements and unresolved exceptions.
• Distinguishing cash recovered from adjustments, cancellations and other balance changes when reporting results.

9. Responsible AI, Confidentiality and Supervisory Controls

• Protecting taxpayer information through approved tools, access restrictions, anonymisation and secure recordkeeping.
• Maintaining human approval, audit trails and quality reviews for AI-assisted case analysis and recommendations.

10. Integrated Enforcement and Debt Management Case Study

• Analysing a simulated debt portfolio, verifying balances and proposing appropriate engagement and recovery actions.
• Developing an operational improvement plan covering priority AI applications, staff capability, safeguards and measurable results.

Practical takeaway: Participants will develop templates for debt segmentation, case prioritisation, payment arrangement monitoring, recovery dashboards and enforcement case reviews.

This short course is aimed at internal auditors, with or without formal qualifications or experience in auditing, who work in an internal audit environment